boat image

Author: basameera

MyCode/Bayes Filter/README.md

@@ -13,6 +13,9 @@
 * Mesurement model
 * Main window
 * Key press plot
+* Main window handling class
+* B. F. calculations
+* draw boat
 
 ### Reference
 

MyCode/Bayes Filter/bayes_filter_viz.py

@@ -0,0 +1,21 @@
+from skylynx.utils import cli_args
+from utils import *
+import matplotlib.pyplot as plt
+import numpy as np
+import matplotlib.image as mpimg
+from matplotlib.offsetbox import TextArea, DrawingArea, OffsetImage, AnnotationBbox
+
+
+class BayesFilterBoat(object):
+
+    def __init__(self):
+        pass
+
+    def hello(self, msg):
+        print(msg)
+
+
+if __name__ == "__main__":
+    
+    boat_bf = BayesFilterBoat()
+    boat_bf.hello('sameera')

MyCode/Bayes Filter/test.py

@@ -2,6 +2,8 @@
 from utils import *
 import matplotlib.pyplot as plt
 import numpy as np
+import matplotlib.image as mpimg
+from matplotlib.offsetbox import TextArea, DrawingArea, OffsetImage, AnnotationBbox
 
 
 def ax_set_settings(ax):
@@ -15,6 +17,15 @@ def ax_set_settings(ax):
 
 
 click_counter = 0
+simulation_scope = 10
+boat = mpimg.imread('/home/sameera/Downloads/sailboat.png')
+
+
+def draw_boat(ax, x=0):
+    global boat
+    imagebox = OffsetImage(boat, zoom=0.2)
+    ab = AnnotationBbox(imagebox, (x, 0.8), frameon=False)
+    ax.add_artist(ab)
 
 
 def get_color_label():
@@ -39,17 +50,33 @@ def onclick(event):
             ax.clear()
             data = np.random.random((10,))
             c, l = get_color_label()
-            ax.scatter(data, data, c=c, label=l)
+            p = [0.5, 0.5, 1]
+            y = norm(p)
+            y = np.concatenate((y, np.zeros(simulation_scope-len(p),)))
+            x = np.arange(simulation_scope)
+
+            bar_plot(ax, x, y, color='tab:blue', label='Init')
+            draw_boat(ax, 2)
             ax_set_settings(ax)
 
             fig.canvas.draw()
             click_counter += 1
 
-    fig, axs = plt.subplots(1, 1, figsize=(14, 5))
+    fig, axs = plt.subplots(1, 1, figsize=(8, 4))
+    global simulation_scope
     ax = axs
 
     cid = fig.canvas.mpl_connect('key_release_event', onclick)
-    ax.plot(np.arange(0, 1, 0.1), c='tab:blue', label='Init')
+
+    # Initial p(x)
+    p = [0.6, 0.5]
+    y = np.array(p)
+    y = np.concatenate((y, np.zeros(simulation_scope-len(p),)))
+    x = np.arange(simulation_scope)
+
+    # ax.plot(np.arange(0, 1, 0.1), c='tab:blue', label='Init')
+    bar_plot(ax, x, y, color='tab:blue', label='Init')
+    draw_boat(ax)
     ax_set_settings(ax)
     plt.show()
 
@@ -59,15 +86,12 @@ def task_2():
     """
 
     fig, axs = plt.subplots(1, 1, figsize=(8, 4))
-
     simulation_scope = 10
 
     # Initial p(x)
     p = [0.5, 0.5]
     y = np.array(p)
-
     y = np.concatenate((y, np.zeros(simulation_scope-len(p),)))
-
     x = np.arange(simulation_scope)
 
     ax = axs

MyCode/Bayes Filter/utils.py

@@ -1,7 +1,7 @@
 import numpy as np
 
 
-def bar_plot(ax, x, y, color=None):
+def bar_plot(ax, x, y, color=None, label=''):
     """Bar Plot
 
     Parameters
@@ -12,15 +12,15 @@ def bar_plot(ax, x, y, color=None):
 
     """
 
-    ax.set_axisbelow(True)
-    ax.grid(ls='--')
-    ax.bar(x, y, color=color, width=0.5)
+    # ax.set_axisbelow(True)
+    # ax.grid(ls='--')
+    ax.bar(x, y, color=color, width=0.5, label=label)
     # plt.xlabel("File names")
     # plt.ylabel("Execution time (seconds)")
     # plt.title("Effects of Numba (loop of 1e6)")
     # plt.xticks(x_pos, x)
     # plt.savefig('stats.pdf')
-    ax.set_ylim(0, 1)
+    # ax.set_ylim(0, 1)
 
 
 def norm(x):